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	91	Convolution Hierarchical Deep-learning Neural Networks (C-HiDeNN): finite elements, isogeometric analysis, tensor decomposition, and beyond Enthalten in Computational mechanics Bd. 72, 16.5.2023, Nr. 2, date:8.2023: 333-362
	92	Correction: Assuring Efficient Path Selection in an IntentBased Networking System: a Graph Neural Networks and Deep Reinforcement Learning Approach Enthalten in Journal of network and systems management Bd. 32, 30.5.2024, Nr. 3, date:7.2024: 1
	93	Correction: Assuring Efficient Path Selection in an Intent-Based Networking System: A Graph Neural Networks and Deep Reinforcement Learning Approach Enthalten in Journal of network and systems management Bd. 32, 2.8.2024, Nr. 4, date:10.2024: 1-2
	94	COVID-19 diagnosis on CT images with Bayes optimization-based deep neural networks and machine learning algorithms Enthalten in Neural computing & applications Bd. 34, 28.2.2022, Nr. 7, date:4.2022: 5349-5365
	95	Data-driven solitons dynamics and parameters discovery in the generalized nonlinear dispersive mKdV-type equation via deep neural networks learning Enthalten in Nonlinear dynamics Bd. 112, 19.3.2024, Nr. 9, date:5.2024: 7433-7458
	96	Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax Enthalten in Scientific reports Bd. 15, 30.1.2025, Nr. 1, date:12.2025: 1-11
	97	Deep learning-based ovarian cyst classification and abnormality detection using convolutional neural networks Enthalten in Neural computing & applications Bd. 37, 10.12.2024, Nr. 5, date:2.2025: 3047-3059
	98	Deep learning neural networks for emotion classification from text: enhanced leaky rectified linear unit activation and weighted loss Enthalten in Multimedia tools and applications Bd. 81, 28.2.2022, Nr. 11, date:5.2022: 15439-15468
	99	Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data Enthalten in Journal of cheminformatics Bd. 9, 28.6.2017, Nr. 1, date:12.2017: 1-13
	100	Deep neural networks watermark via universal deep hiding and metric learning Enthalten in Neural computing & applications Bd. 36, 21.2.2024, Nr. 13, date:5.2024: 7421-7438

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